ClickClack is a production-grade, self-hostable team chat platform built for people, bots, and agents. The backend is a single Go binary serving a REST API with WebSocket real-time events, supporting both SQLite and PostgreSQL as interchangeable storage backends. The frontend is a Svelte 5 single-page application embedded into the Go binary, with an optional Electron desktop client and a TypeScript SDK for bot development. The system provides workspaces, channels, threads, direct messages, file uploads, full-text search, reactions, pinned messages, slash commands, event subscriptions, and push notifications (Web Push and Pushover). Authentication supports magic links, passwords (Argon2id), GitHub OAuth, and Cloudflare Access JWT. The architecture emphasizes security with SSRF-safe callback dialers, strict cookie namespacing, rate limiting, and bot scope enforcement. The codebase is notable for its dual-database store pattern with shared contract tests, a real-time event hub with cursor-based recovery, and a comprehensive test suite including unit, integration, and Playwright end-to-end tests. It is not a data research project; it is a fully featured application designed for self-hosting or cloud deployment.
This repository provides a comprehensive Nginx security configuration package to block malicious bots, spam referrers, bad IPs, and vulnerability scanners. It includes curated blocklists (bad user agents, referrers, IPs, fake Googlebots), rate limiting/DDoS protection, and optional fail2ban integration. The core deliverable is a set of modular Nginx include files (bots.d/, conf.d/) and shell scripts (install-ngxblocker, setup-ngxblocker, update-ngxblocker) for automated deployment and daily updates. It also generates Google Analytics ghost spam exclusion lists and a Google Search Console disavow file. The architecture is a collection of configuration templates and deployment tooling, not a standalone application; it is designed to be included into existing Nginx server blocks. The repository is actively maintained with frequent updates to blocklists and CI testing across multiple Linux distributions.
This is a cross-platform software development kit (SDK) for rendering Adaptive Cards—a JSON-based card format used by Microsoft products like Teams, Outlook, and Cortana. The repository provides a shared C++ object model for parsing and serializing card definitions, along with platform-specific renderers for Android, iOS, UWP (WinUI), .NET (WPF), and Node.js. It also includes a templating engine for dynamic data binding, a visual designer tool, and multiple test applications. The architecture is a library/framework model: each platform has its own rendering layer that converts the parsed card model into native UI components. The codebase is large and well-organized, with clear separation between the shared model and platform implementations. However, feature parity across platforms is incomplete (e.g., v1.5 features are missing in .NET renderer), and there is significant duplication of logic across platforms, which introduces maintenance risk.
Botright is a Python library built on Playwright that provides advanced browser automation with stealth features to evade bot detection. It includes proxy management, fingerprint spoofing using real browser profiles (chrome-fingerprints), human-like mouse movements, and CAPTCHA solving for hCaptcha, reCAPTCHA, and Geetest (though Geetest support is currently disabled). The library wraps Playwright's API with a custom layer that intercepts browser events, modifies user agent, platform, and other fingerprinting vectors, and injects anti-detection scripts. It supports both headless and headed modes, proxy rotation, and response caching. The codebase is well-structured but has commented-out modules indicating incomplete transitions (e.g., Geetest).
This repository is primarily a large collection of GPT prompt templates (markdown files) designed for use with AI chat platforms like FlowGPT or gptcall.net. Each prompt file defines a specific role or task for the AI, such as a resume editor, coding tutor, fitness planner, or creative writing assistant. The repository also includes an Android application (OpenClaw and Codex) referenced in the README, along with Node.js scripts (update.mjs, db.mjs) for managing the prompt data. The prompts are structured with placeholders for user input and often request specific output formats, enabling users to import them into chat interfaces to obtain specialized AI behavior without crafting prompts from scratch. While the prompt library is extensive, it contains significant duplication, minimal-effort entries, and some policy-risking content (e.g., jailbreaks, NSFW role-play), which affects overall quality and reuse potential.